Senior Data Engineer

Gen II Fund Services; Boca Raton (FL); Hybrid; USD 140,000 - 170,000; Full time

Benefits offered by this job

Discretionary bonus

Comprehensive benefits package

Job summary

Gen II Fund Services is looking for a Senior Data Engineer to manage the data layer delivery in their Data & Integration Platform. This role involves building and maintaining data layers within Snowflake while ensuring data quality and efficient processing.

Candidates should possess 5+ years of data engineering experience and strong Snowflake and Python skills. The role has a hybrid work arrangement requiring some in-office presence. Salary ranges from $140,000 to $170,000 plus benefits.

Qualifications

• 5+ years of hands-on data engineering experience.
• Deep practical Snowflake expertise including data modelling and SQL optimisation.
• Strong Python development skills for data processing scripts.

Responsibilities

• Build and maintain Bronze to Gold layers within Snowflake.
• Develop and maintain Snowflake Streams, Tasks, and Stored Procedures.
• Structure Gold-layer outputs for Power BI and Qlik.

Skills

Snowflake expertise

Python development

Data governance knowledge

AI-assisted development

BI tooling experience

Education

Bachelor's or Master's degree in Computer Science or related field

Tools

Fivetran

Power BI

Qlik

Job description

Gen II is a leading fund administration provider focused on private capital asset managers and investors, managing more than $1.5 trillion in private fund capital assets.

Job Summary

We are building out our Data & Integration Platform (DIP)—the central data backbone that powers data integration, analytics, reporting, and AI capabilities across our fund administration technology estate. At the heart of DIP is a Snowflake‑based medallion data architecture—Bronze, Silver, and Gold—fed by integrations across 40+ systems and consumed by business intelligence, client‑facing products, and AI‑driven services. This role is for a Senior Data Engineer who will own the data layer delivery, build and maintain the Bronze, Silver, and Gold layers, and drive data workstreams with minimal oversight.

Snowflake Data Layer Build

• Build and maintain Bronze to Gold layers within Snowflake—moving data for reporting, analytics, and egress.
• Design and implement Snowflake data models aligned to Gen II’s canonical domain model—fund structures, investors, GL, NAV, compliance.
• Develop and maintain Snowflake Streams, Tasks, and Stored Procedures for pipeline orchestration and incremental processing.
• Own data quality—implement validation, monitoring, and alerting within the pipeline to ensure Gold‑layer data is trustworthy.
• Work with Fivetran‑synced data from source systems and Snowflake Secure Data Shares, building clean ingestion patterns at the Bronze/Silver boundary.

AI‑Assisted Development

• Use AI tooling (LLMs, codegen, Claude) across all data engineering work—generating transformation SQL, scaffolding Python scripts, producing test cases, automating documentation.
• Contribute to a data factory approach—reusable, metadata‑driven patterns for transformation, testing, and deployment that can be applied consistently across data streams.

Python & Streamlit Development

• Build Streamlit applications in Snowflake for internal operational tooling—data review queues, reconciliation dashboards, client provisioning workflows, and similar.
• Write Python scripts and utilities to support data processing, validation, and operational tasks within the DIP ecosystem.
• Contribute to pytest‑based test suites for data pipeline validation, aligned to DIP QA standards.

Analytics & BI Enablement

• Structure Gold‑layer outputs to serve downstream consumers—Power BI, Qlik, and client‑facing analytics products.
• Collaborate with BI specialists to ensure data models support reporting requirements without duplication or technical debt.
• Support the establishment of master data management and golden record patterns across key fund administration entities.

Delivery & Collaboration

• Take data workstreams from requirement to production with minimal hand‑holding.
• Work closely with the Associate Director of Data Engineering, integration engineers, BAs, and QA—raising blockers early and documenting decisions clearly.
• Collaborate with integration engineers to ensure data lands cleanly at the Bronze/Silver boundary and conforms to agreed schemas.
• Contribute to data governance practices—lineage, cataloguing, access control, and data quality standards.

Qualifications

• 5+ years of hands‑on data engineering experience.
• Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field.
• Deep practical Snowflake expertise—data modelling, SQL optimisation, Streams/Tasks/Stored Procedures, Secure Data Shares; SnowPro certification a plus.
• Strong Python development skills—data processing scripts, utilities, and Streamlit applications.
• Experience building Bronze/Silver/Gold medallion architectures or equivalent layered data warehouse patterns.
• Hands‑on experience with Fivetran or equivalent ELT tooling for source system ingestion desired.
• Active use of AI‑assisted development in data engineering delivery—transformation generation, test scaffolding, documentation automation.
• Experience with BI tooling—Power BI and/or Qlik—and structuring data models to serve reporting consumers effectively.
• Ability to own workstreams independently and drive delivery without close management.
• Experience with data governance, data quality frameworks, and master data management (desirable).
• Exposure to fund administration, private capital, or broader financial services environments (desirable).
• Familiarity with AI/ML concepts and their application to financial services data (desirable).
• Strong communication skills and ability to collaborate across technical and business teams.

Compensation

The salary range for this position is $140,000 – $170,000, in addition to a discretionary bonus and a comprehensive benefits package. The actual salary offered within that range will depend on the candidate’s experience level.

Work Arrangement

This role follows a flexible hybrid schedule, with the resource expected in the office 1‑4 days per week on a need basis. All applicants must be legally authorized to work in the United States.